Fuzzy multi-objective modelling for managing water-food-energy-climate change-land nexus towards sustainability

[Display omitted] •A novel water-food-energy-climate change-land (WORLD) nexus perspective is found.•A Me-measure-based fuzzy multi-objective nonlinear programming method is developed.•The method is applied to the WORLD nexus system of Zhanghe irrigation district, China.•Connections, synergies, and...

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Published in:Journal of hydrology (Amsterdam) Vol. 596; p. 125704
Main Authors: Yue, Qiong, Zhang, Fan, Wang, Youzhi, Zhang, Xiaoxing, Guo, Ping
Format: Journal Article
Language:English
Published: Elsevier B.V 01.05.2021
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ISSN:0022-1694, 1879-2707
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Abstract [Display omitted] •A novel water-food-energy-climate change-land (WORLD) nexus perspective is found.•A Me-measure-based fuzzy multi-objective nonlinear programming method is developed.•The method is applied to the WORLD nexus system of Zhanghe irrigation district, China.•Connections, synergies, and tradeoffs in the WORLD nexus system are quantified.•Decision supports for coordinated management of WORLD nexus system is provided. Water, food, energy, climate change and land subsystems are closely intertwined, and play remarkable roles in regional resources management system. Quantification of connections, synergies, and tradeoffs across these subsystems is needed in a more integrated and comprehensive manner, which is challenging due to the complexities and uncertainties involved therein. This paper proposed an inexact optimization approach from a novel water-food-energy-climate change-land (WORLD) nexus perspective, which has potential to promote social-economic development, guarantee livelihood security, and achieve low-carbon target. The approach is capable of (1) helping decision makers identify optimal policy alternatives among water, land, and energy, balancing economic benefit, water supply guarantee rate, hydroelectric generation, water-land utilization, crop yield, and greenhouse gas emission, via a multi-objective non-linear optimization model; (2) providing decision makers insights into in-depth analysis of optimal water-land resources allocation strategies associated with different levels of water supply, optimistic-pessimistic attitude, and climate change and where the effort could be made towards regional sustainability; (3) dealing with fuzzy uncertainties simultaneously occurring in objective functions and constraints as well as tracking fluctuating attitudes of decision-makers. The effectiveness of proposed model was verified in a real-world case in Zhanghe Irrigation District, Hubei Province, China. The changing range of economic benefit, crop yield, energy production, and environmental impacts were obtained based on optimal water-land resources allocation under different confidence levels and risk attitudes. Results under climate change scenarios show that climate change exacerbated local water shortage, especially in RCP 8.5, which requires 4.24 × 108 m3 of compensatory external water. Results also show that CO2 emission contributed 94.9% of GHGs emission, while fertilizers application contributed to 58% of total CO2 emission amount, calling for effective fertilizer utilization management. Compared with single objective models, proposed model performs better on providing coordinated policy solutions. The proposed approach can help manage resources in WORLD nexus system in a sustainable way, and is portable to other similar regions to promote sustainable development.
AbstractList [Display omitted] •A novel water-food-energy-climate change-land (WORLD) nexus perspective is found.•A Me-measure-based fuzzy multi-objective nonlinear programming method is developed.•The method is applied to the WORLD nexus system of Zhanghe irrigation district, China.•Connections, synergies, and tradeoffs in the WORLD nexus system are quantified.•Decision supports for coordinated management of WORLD nexus system is provided. Water, food, energy, climate change and land subsystems are closely intertwined, and play remarkable roles in regional resources management system. Quantification of connections, synergies, and tradeoffs across these subsystems is needed in a more integrated and comprehensive manner, which is challenging due to the complexities and uncertainties involved therein. This paper proposed an inexact optimization approach from a novel water-food-energy-climate change-land (WORLD) nexus perspective, which has potential to promote social-economic development, guarantee livelihood security, and achieve low-carbon target. The approach is capable of (1) helping decision makers identify optimal policy alternatives among water, land, and energy, balancing economic benefit, water supply guarantee rate, hydroelectric generation, water-land utilization, crop yield, and greenhouse gas emission, via a multi-objective non-linear optimization model; (2) providing decision makers insights into in-depth analysis of optimal water-land resources allocation strategies associated with different levels of water supply, optimistic-pessimistic attitude, and climate change and where the effort could be made towards regional sustainability; (3) dealing with fuzzy uncertainties simultaneously occurring in objective functions and constraints as well as tracking fluctuating attitudes of decision-makers. The effectiveness of proposed model was verified in a real-world case in Zhanghe Irrigation District, Hubei Province, China. The changing range of economic benefit, crop yield, energy production, and environmental impacts were obtained based on optimal water-land resources allocation under different confidence levels and risk attitudes. Results under climate change scenarios show that climate change exacerbated local water shortage, especially in RCP 8.5, which requires 4.24 × 108 m3 of compensatory external water. Results also show that CO2 emission contributed 94.9% of GHGs emission, while fertilizers application contributed to 58% of total CO2 emission amount, calling for effective fertilizer utilization management. Compared with single objective models, proposed model performs better on providing coordinated policy solutions. The proposed approach can help manage resources in WORLD nexus system in a sustainable way, and is portable to other similar regions to promote sustainable development.
Water, food, energy, climate change and land subsystems are closely intertwined, and play remarkable roles in regional resources management system. Quantification of connections, synergies, and tradeoffs across these subsystems is needed in a more integrated and comprehensive manner, which is challenging due to the complexities and uncertainties involved therein. This paper proposed an inexact optimization approach from a novel water-food-energy-climate change-land (WORLD) nexus perspective, which has potential to promote social-economic development, guarantee livelihood security, and achieve low-carbon target. The approach is capable of (1) helping decision makers identify optimal policy alternatives among water, land, and energy, balancing economic benefit, water supply guarantee rate, hydroelectric generation, water-land utilization, crop yield, and greenhouse gas emission, via a multi-objective non-linear optimization model; (2) providing decision makers insights into in-depth analysis of optimal water-land resources allocation strategies associated with different levels of water supply, optimistic-pessimistic attitude, and climate change and where the effort could be made towards regional sustainability; (3) dealing with fuzzy uncertainties simultaneously occurring in objective functions and constraints as well as tracking fluctuating attitudes of decision-makers. The effectiveness of proposed model was verified in a real-world case in Zhanghe Irrigation District, Hubei Province, China. The changing range of economic benefit, crop yield, energy production, and environmental impacts were obtained based on optimal water-land resources allocation under different confidence levels and risk attitudes. Results under climate change scenarios show that climate change exacerbated local water shortage, especially in RCP 8.5, which requires 4.24 × 10⁸ m³ of compensatory external water. Results also show that CO₂ emission contributed 94.9% of GHGs emission, while fertilizers application contributed to 58% of total CO₂ emission amount, calling for effective fertilizer utilization management. Compared with single objective models, proposed model performs better on providing coordinated policy solutions. The proposed approach can help manage resources in WORLD nexus system in a sustainable way, and is portable to other similar regions to promote sustainable development.
ArticleNumber 125704
Author Zhang, Xiaoxing
Wang, Youzhi
Guo, Ping
Yue, Qiong
Zhang, Fan
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  fullname: Wang, Youzhi
  organization: Centre for Agricultural Water Research in China, China Agricultural University, Beijing 100083, China
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  surname: Zhang
  fullname: Zhang, Xiaoxing
  organization: Centre for Agricultural Water Research in China, China Agricultural University, Beijing 100083, China
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  givenname: Ping
  surname: Guo
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Keywords Uncertainty
Water-food-energy-climate change-land nexus
Sustainability
Multi-objective modelling
Me-measure fuzzy chance-constrained programming
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Snippet [Display omitted] •A novel water-food-energy-climate change-land (WORLD) nexus perspective is found.•A Me-measure-based fuzzy multi-objective nonlinear...
Water, food, energy, climate change and land subsystems are closely intertwined, and play remarkable roles in regional resources management system....
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StartPage 125704
SubjectTerms carbon dioxide
China
climate change
crop yield
decision making
energy
fertilizers
financial economics
greenhouse gas emissions
hydrology
irrigation
issues and policy
livelihood
management systems
Me-measure fuzzy chance-constrained programming
Multi-objective modelling
risk
Sustainability
sustainable development
Uncertainty
water shortages
Water-food-energy-climate change-land nexus
Title Fuzzy multi-objective modelling for managing water-food-energy-climate change-land nexus towards sustainability
URI https://dx.doi.org/10.1016/j.jhydrol.2020.125704
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